The Educator Experience with AI: Beyond Scope and Sequence

Research Brief | MediaEd Insights | AI: Educator Perspectives Edition | June 2026

Written by Glen Warren

Artificial intelligence is challenging education, but perhaps not in the ways many of us expected.

Much of the conversation is focused on tools, skills, and freedoms. How should students use AI? What policies should schools adopt? How do we address academic integrity? What new skills are required?

These are important questions.

Yet as I work with students and educators, I find myself focused on a different concern. AI is surfacing strengths we have long valued and weaknesses we have often overlooked. Most of these did not begin with AI. AI is simply making them harder to ignore.

For decades, education has focused heavily on Scope and Sequence. We devote considerable attention to determining what students should learn and when they should learn it. Standards, curriculum maps, pacing guides, and assessments are all designed to support this work.

This approach has value. Knowledge matters. Skills matter. Learning should build over time.

But AI is revealing the importance of something else.

Not just Scope and Sequence, but People and Purpose.

Who are students becoming through their learning? Why does their learning matter?

These questions have always been important, but they are becoming increasingly difficult to ignore.

A student interacting with an AI system may receive information instantly. They may generate ideas, summaries, images, or even entire products in seconds. Yet the most important questions are often no longer about getting an answer or completing an assignment in adherence to a rubric. They are about judgment, meaning, relevance, and responsibility.

Why should I trust this? Whose perspective might be missing? Who might be impacted by sharing this information? Why should I care as a consumer and creator of information?

These are not purely AI literacy questions. They are information literacy questions. They are media literacy questions. And increasingly, they are human questions.

As schools rush to implement AI literacy initiatives, there is a risk of treating AI literacy as something separate and new. I would argue the opposite.

Effective AI literacy is not separate from information literacy and media literacy. It is built upon them.

When those foundations are weak, AI literacy efforts are a house built on sand.

At the same time, AI is reminding us that literacy alone is not enough. Students must also develop the curiosity to ask questions, the care to consider impact, and the connection to understand how ideas, people, and systems influence one another.

This realization inspired the development of I.A.M. (Information, AI, and Media Literacy): A Curious Skeptic Toolkit for a Connected World.

I.A.M. is designed to help educators bring these literacies together rather than treating them as competing initiatives. It provides practical ways to embed information, media, and AI literacy into learning that is already taking place while helping students connect knowledge to meaning and responsibility.

The future of education will still require Scope and Sequence.

But the age of AI is reminding us that education must also attend to People and Purpose.

Because the ultimate goal is not simply helping students know more.

It is helping them become thoughtful, informed, and responsible people in a connected world.

Research Spotlight: Three Questions Shaping the Future of AI in Education

As educators explore the opportunities and challenges of AI, researchers across information literacy, media literacy, learning science, and cognitive psychology are investigating several important questions.

Does access to information lead to understanding?

Research from scholars including Daniel Willingham, Sam Wineburg, and Renée Hobbs reminds us that access to information does not automatically produce understanding or sound judgment. As AI makes information instantly available, the educational challenge shifts from finding information to evaluating evidence, recognizing perspective, making connections, and applying knowledge thoughtfully.

Can students transfer learning across contexts?

Learning scientists such as John Bransford, David Perkins, Gavriel Salomon, and Daniel Willingham have spent decades studying transfer—the ability to apply learning in new situations. Their work consistently shows that transfer is difficult. AI may become one of education’s greatest transfer tests, requiring students to apply information literacy, media literacy, critical thinking, and ethical reasoning beyond the lessons in which they were originally taught.

Which human capacities become more important as AI becomes more capable?

Researchers including Renée Hobbs, Carol Dweck, Howard Gardner, and Yong Zhao continue to explore the human dimensions of learning. As AI performs more cognitive tasks, educators are increasingly asking which qualities become more—not less—essential. Curiosity, judgment, creativity, empathy, civic responsibility, and purpose are emerging as capacities that help learners navigate an increasingly intelligent and connected world.

A common thread emerges across these fields: AI is not replacing information literacy or media literacy. Instead, it is revealing why both are more important than ever and why helping students connect knowledge to meaning, responsibility, and purpose remains one of education’s central challenges.